As all structures in service may require appropriate inspection and maintenance, they should be monitored for their integrity and health condition to extend their life or to prevent catastrophic failure. Numerous techniques have been employed to identify fault or damage of structures. Such techniques include conventional visual inspection and non-destructive automated techniques including ultrasonic and eddy current scanning, acoustic emission and X-ray inspection. Such conventional techniques often require at least temporary removal of structures from service for inspection. Although still widely used for inspection of isolated locations, they are often time-consuming and expensive and may not be suitable on their own for inspecting equipment such as aircraft while the equipment is in service.
Such approaches have other drawbacks and may not provide effective on-line methods to implement a reliable sensory network system and/or accurate monitoring methods that can diagnose, classify and/or forecast structural condition with minimum intervention of human operators.
With the advance of sensor technologies, new diagnostic techniques for in-situ structural integrity monitoring have made significant progress. Typically, these new techniques utilize sensory systems of appropriate sensors and actuators built into host structures.
Some SHM systems use “passive” strain tracking or acoustic emission monitoring techniques. However, to effectively detect damage in many applications, both passive strain tracking and passive acoustic emission monitoring techniques may require continuous monitoring. Accordingly, if a power failure or power shut-down occurs, the SHM system may be disabled—which can be a disadvantage. Moreover, both passive strain tracking and passive acoustic emission monitoring may not be as sensitive as desired, and therefore may be less accurate and/or reliable. The accuracy and reliability of acoustic emission monitoring techniques may also be compromised by the generally noisy environment of a vehicle or other environment. Another possible disadvantage of acoustic emission monitoring is that a large amount of data storage may be necessary. To quantify and localize the damage, the strain tracking technique may require a finite element strain distribution model with which to compare the measured strain distribution across the structure, possibly increasing development cost.
Other SHM systems may be considered “active” systems because they use transducers to actively excite and sense vibrational characteristics of the structure. The vibrational characteristics can be compared with known or baseline (and thus predetermined) vibrational characteristics of a normal undamaged structure; and the difference(s) is used to determine the health of the structure. Specifically, in some SHM systems, the vibrational characteristics can be defined by computing the transfer function between each actuator and sensor. The transfer functions can then be compared to a baseline reference representing a normal “healthy” state of the structure. The baseline may be generated by collecting several sets of actuator/sensor data when the structure is healthy, and computing statistical values such as the mean and standard deviation of the data sets. However, temperature variations of the structure may sometimes cause these active SHM systems to erroneously detect damage. Specifically, temperature variations in the structure may cause variations in the measured vibrational characteristics that carry over into the transfer functions computed therefrom.
Known techniques often follow one of two approaches: signal excitation and processing on the one hand, and on the other hand, worked signal and results.
For example, methods are known that detect changes of damping characteristics of vibrational waves in a laminated composite structure to locate delaminated regions in the structure. Piezoceramic devices can be applied as actuators to generate the vibrational waves, and fiber optic cables with different grating locations can be used as sensors to catch or sense the propagating wave signals. A possible drawback of this type of system is that it cannot accommodate a large number of actuator arrays and, as a consequence, each of actuators and sensors must be placed individually. Since the damage detection is based on changes of vibrational waves traveling along line-of-sight paths between the actuators and sensors, such a method may fail to detect the damage located out of the paths and/or around the boundary of the structure.
Another known approach for damage detection uses a self-contained conformal circuit for structural health monitoring and assessment. Such a conformal circuit may for example consist of a series of stacked layers and traces of strain sensors, where each sensor measures strain changes at its corresponding location to identify defects of a conformal structure. The conformal circuit may for example comprise a passive system, i.e., it does not have any actuator for generating signals. Another example passive sensory network system may use a piezoceramic-fiber sensory system having planer fibers embedded in a composite structure.
A possible drawback of these and other passive methods is that they cannot monitor internal delamination and damage between the sensors. Moreover, these methods can typically detect the conditions of their host structures only in the local areas where the self-contained circuit and the piezoceramic-fiber are affixed.
Another interesting method for detecting damages in a structure uses a sensory network layer, called Stanford Multi-Actuator-Receiver Transduction (SMART) Layer. The SMART Layer® includes piezoceramic sensors/actuators equidistantly placed and cured with flexible dielectric films sandwiching the piezoceramic sensors/actuators (“piezoceramics”). The actuators generate acoustic waves and sensors receive/transform the acoustic waves into electric signals. To connect the piezoceramics to an electronic box, metallic clad wires are etched using conventional flexible circuitry and laminated between the substrates. As a consequence, a considerable amount of the flexible substrate area may be needed to cover the clad wire regions. In addition, the SMART Layer® may need to be cured with its host structure made of laminated composite layers. Due to the internal stress caused by a high temperature cycle during the curing process, the piezoceramics in the SMART Layer® can be micro-fractured. Also, the substrate of the SMART Layer® can sometimes be easily separated from the host structure. Moreover, it can be very difficult to insert or attach the SMART Layer® to its host structure having a curved section and, as a consequence, a compressive load applied to the curved section can sometimes easily fold the clad wires. Fractured piezoceramics and the folded wires may be susceptible to electromagnetic interference noise and provide misleading electrical signals. In harsh environments, such as thermal stress, field shock and vibration, the SMART Layer® may not necessarily be a robust and unreliable tool for monitoring structural health. Furthermore, the replacement of damaged and/or defective actuators/sensors may sometimes be costly as the host structure may need to be dismantled.
Another known actuator and sensor system is known for use with composite structures, especially carbon-fiber reinforced plastic structures with piezo-ceramic actuators, particularly for active vibration dampening and/or shape control purposes, as well as fiber Bragg grating sensors, particularly in the form of strain measurement sensors. The piezo-ceramic actuators are designed as piezo fiber modules and the fiber Bragg grating sensors are at least partially embedded in the piezo fiber modules. Yet another known interrogation systems for monitoring structural health conditions includes at least one wave generator for generating a wave signal and optical fiber sensors applied to a structure. The interrogation system also includes at least one electronic module for generating an input sensor signal and sending the input sensor signal to the optical fiber sensors. Each optical fiber sensor impresses the wave signal onto the input sensor signal to generate an output sensor signal that is frequency shifted from the input sensor signal. The electronic module generates an information signal in response to the output sensor signal. The interrogation system also includes a signal processing unit and a relay switches array module. Each relay switch relays the information signal to the signal processing unit and the signal processing unit generates a digital sensor signal that is subsequently sent to a computer.
Yet another known method for monitoring damage to a structure having an actuator and a sensor includes exciting the actuator across a predetermined frequency range to excite the structure, measuring a vibrational characteristic of the structure across the predetermined frequency range in response to the excitation of the actuator using the sensor, calculating a transfer function for the actuator and the sensor using the measured vibrational characteristic, determining a change in the vibrational characteristic across the predetermined frequency range using the transfer function, and analyzing the determined change in the vibrational characteristic across the predetermined frequency range to facilitate determining whether the structure is damaged.
Other known devices for monitoring structural health conditions of host structures include at least one optical fiber sensor and an electronic module. The optical fiber sensor includes a rolled optical fiber cable operative to generate a frequency shift of a light signal passing through the optical fiber and a coating layer applied to the rolled optical cable. The frequency shift is commensurate with vibration of the host structure. The electronic module sends an input light signal to the optical fiber sensor, receives a sensor signal from the optical fiber sensor, and processes the sensor signal.
Yet another known method for optimizing transducer performance in an array of transducers in a structural health monitoring system includes specifying a plurality of paths between pairs of the transducers on a monitored structure and evaluating the quality of signal transmissions along the paths so as to optimize the gain and frequency operating condition of the transducers.
In yet another known method for diagnosis of a structure, at least one electromechanical transducer is fixed to a structure as an object of diagnosis and is driven with an alternating voltage of a constant amplitude, and a current flowing through the at least one electromechanical transducer is measured. Next, high frequency components around a driving frequency of the electromechanical transducer are separated from a signal of the current. Next, modulation information due to a damage is extracted from amplitude and/or phase demodulation of the high frequency components. Then a damage index is evaluated based on the modulation information. Thus, structural health can be diagnosed with use of at least one electromechanical transducer, without baseline data, in one measurement.
Yet another known method relates to testing structures or bodies to determine if they contain defects such as cracks or delamination. Such a method for testing a body comprises the steps of comparing first data, representing an excitation signal launched into the body to produce a guided wave within the body, with second data, derived from the body while bearing the guided wave, to identify a phase difference between the first and second data; and determining a measure of the structural integrity of the body using the phase difference. It is alleged that by basing the assessment of the structural body on defect induced phase modulation, more accurate testing can be performed.
Another known structural health monitoring system, for example a system used in the non-destructive evaluation of an aircraft structure provides a method and apparatus for evaluating one or more anomalies within a structure using a structural health monitoring system that includes at least three transducers arranged in operative contact with the structure such that no two transducers are aligned to be parallel. A transducer excites an elastic wave that propagates through the structure, and reflections from any anomalies within the structure are collected by the three transducers. These collected signals are analyzed to identify an anomaly within the structure. Time of flight techniques are used to determine the location of the anomaly.
The working of the signal envisaged in non-limiting example embodiments herein is unique at least because the signal working involves matching phase and amplitude, while many other known techniques are directed for the working of phase alone or amplitude alone. By matching phase and amplitude, many advantages are obtained, such as much finer resolution for the strain measurement with the Bragg grating sensors. These features are summarized in Tables 1 and 2 below.
TABLE 1SIGNAL EXCITATION AND PROCESSINGSIGNAL EXCITATIONSIGNAL PROCESSINGMechanicalAcousticTime ofStatisticalNeuralVibrationElectricityEmissionsFlightAnalysesNetworksTechnique 1xxTechnique 2xxTechnique 3xxTechnique 4xxxTechnique 5xxTechnique 6xxTechnique 7xxTechnique 8xxTechnique 9xxExample Non-xxxLimitingEmbodiments Herein
TABLE 2WORKING OF SIGNAL AND RESULTSWORKING OF SIGNALMatchedPhase andRESULTSFreq.AmplitudePhaseAmplitudeDetectionLocationSeverityTechnique 1xxTechnique 2xxxxTechnique 3xxxTechnique 4xxxxTechnique 5xxTechnique 6xxTechnique 7xxxTechnique 8xxTechnique 9xxExample Non-xxxxLimitingEmbodimentsHerein